3D Wedding Reconstruction & VR Visualization Project

Project Overview & Vision

This project was conceptualized as an experimental research initiative — blending cinematic storytelling, computer vision, and immersive 3D reconstruction — with the vision to build a next-generation platform for reliving and recreating personal memories, especially weddings.

Our goal was to explore how AI, 3D reconstruction, and VR technologies could be combined to create a more emotional and interactive storytelling experience.
We wanted to develop a system capable of transforming real-life video footage and images into 3D, game-like environments that users could freely explore — similar to moving inside an open-world environment like GTA Vice City.

We approached this concept in two ways:

Real-time 3D Capture (Pre-wedding / During Events):
We wanted to build a setup capable of capturing live scenes using computer vision and 3D reconstruction. The idea was to record authentic human interactions — emotions, gestures, and body movement — and convert them into dynamic, explorable 3D spaces.
Post-event 3D Recreation (Reimagined Weddings):
We also wanted to make this accessible for people who, at the time of their marriage, could not celebrate it grandly. Our idea was to recreate their event virtually, constructing a 3D world representation of their wedding using captured images, videos, and AI-based scene reconstruction.
In this virtual world, couples could experience their dream wedding as if it truly happened — complete with customized environments, relatives, and interactions.

Through this, our vision was to bridge emotion and technology — turning personal memories into immersive 3D experiences using computer vision, structure-from-motion (SfM), and VR visualization techniques.

This project remains a prototype and research-based exploration, with several challenges still under active experimentation, especially in dynamic point cloud capture and real-time motion reconstruction.

Collaboration

This project was developed through a collaboration that blended creative and technical expertise.

The concept and vision were proposed by my collaborator, a professional film and live editor with extensive experience in the Telugu film industry (Tollywood).

He provided the footage and creative feedback, helping shape the scenes based on audience perspective and storytelling flow.

I handled the complete technical execution — including 3D reconstruction, multi-camera setup, and visualization pipeline — transforming the captured footage into interactive and immersive experiences.

Collaboration partner on set with Tollywood actors during film shoots.

Nagarjuna Akkineni | Varun Tej

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Role & Responsibilities: Technical Lead

As the sole technical contributor, I was responsible for the end-to-end technical implementation of the project, combining computer vision, 3D reconstruction, and VR visualization.
Rather than building everything from scratch, I strategically leveraged established, professional-grade software to achieve high-quality outputs efficiently.

Key Contributions:

1. Data Capture & Camera Strategy

Managed DSLR cameras, mobile cameras, drones, and CCTV/multi-camera rigs.
Designed optimal capture strategies: multiple angles, high overlap (60–70%), and uniform lighting.
Balanced use of drones, DSLRs, smartphones, and CCTV cameras for both quality and cost-efficiency.
Proved that high-clarity CCTV images can yield accurate reconstructions while being scalable and budget-friendly.

2. 3D Reconstruction & Processing

Generated live and static point clouds, optimized camera poses, and reconstructed 3D scenes using:

COLMAP, Agisoft Metashape, RealityCapture, Pix4Dmapper, Meshroom (AliceVision), Autodesk ReCap Photo, and OpenMVG + OpenMVS.
Evaluated camera performance: measured how many 3D points each image generated.
Improved efficiency by achieving better reconstructions with fewer input images.
Processed outputs for VR visualization, and cinematic rendering in Adobe After Effects.

3. Dynamic Point Cloud Capture & Multi-Camera Techniques

Focused on capturing dynamic/moving point clouds to represent real-time motion and human interaction.
Developed and tested multi-camera setups (e.g., Logitech Mevo and similar rigs) to record synchronized viewpoints.
Processed individual camera streams, merging them to form consistent dynamic point clouds.
Although real-time playback of dynamic clouds remained partially unresolved, this phase provided valuable insights into motion capture limits and multi-view synchronization.

4. Visualization & Integration

Converted reconstructed 3D environments into interactive HTML/VR scenes viewable on both mobile and desktop.
Integrated 3D assets into Adobe After Effects for stylized visualizations.
Created print-ready 3D models for physical replicas and demonstrations.

Project Demos

Note: These are limited demos showcasing part of the project workflow.
Complete datasets and internal methods are not shared publicly for confidentiality.

🎥 Video Demonstration

Notes / Disclaimers

Only selected demo videos and reference images are shared for privacy and intellectual property reasons.
The project showcases the ability to blend creativity and engineering, solving real-world challenges in computer vision and immersive media.

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